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I don't know if the splat is exactly the same, but the playcanvas engine has no false transparency on this one: https://superspl.at/scene/7e4e9bcb that splat is actually of fairly high quality, so unless this is a materially different splat (with some of the gaussians dropped out maybe?) I'm inclined to blame the engine.

Both use LPDDR5x, they're not shipping LPDDR6 (yet).

Looks neat! I'd love for it to feed the MIDI notes back into my player piano instead of playing out of my iPhone's (comparatively tinny) speakers though.

Hi, security professional here! A lot of the time, we don't need it.

The central point of this app is to determine proximity of two devices. That's not possible today in a cross-platform way using web apps.

The Quick 861DW has been a hobbyist favorite for a long time, and comes in at ~$300 (USD)

For modern systems, stack buffer overflow bugs haven't been great to exploit for a while. You need at least a stack cookie leak and on Apple Silicon the return addresses are MACed so overwriting them is a fools errand (2^-16 chance of success).

Most exploitable memory corruption bugs are heap buffer overflows.

Yep! 60t/s on the 8 bit MLX on an M4 Pro with 64GB of RAM.

There's MLX versions of the model, so yes. LM Studio hasn't updated their mlx-lm runtime yet though, you'll get an exception.

But if you're OK running it without a UI wrapper, mlx_lm==0.30.0 will serve you fine.

It means more surface (both from extensions themselves and the loader code), relaxation of things like KTRR/CTRR (you now need to add executable EL1 pages at runtime), plus the potential for signing keys to leak (Finding enterprise signing keys even for iOS is fairly easy).

As far as Windows goes, https://www.loldrivers.io is a thing.

I do vulnerability research. Those things would do the exact opposite of what you're aiming for. They'd be received with glee by mercenary spyware companies, _especially_ being able to load things into higher levels of privilege.

You're confusing your opinion of the company with the perception by the general public. Apple's definitely not perceived as 'an office appliance company' by your average person. It's considered a high-end luxury brand by many[1].

1: https://www.researchgate.net/publication/361238549_Consumer_...

It'd run on a 5090 with 32GB of VRAM at fp8 quantization which is generally a very acceptable size/quality trade-off. (I run GLM-4.5-Air at 3b quantization!) The transformer architecture also lends itself quite well to having different layers of the model running in different places, so you can 'shard' the model across different compute nodes.

From what I've been reading the inference workload tends to ebb and flow throughout the day with much lower loads overnight than at for example 10AM PT/1PM ET. I understand companies fill that gap with training (because an idle GPU costs the most).

So for data centers, training is just as important as inference.

I believe they mean the source region's tag, rather than the destination.

I have some inside knowledge here. KPP was released around the time KTRR on A11 was implemented to have some small amount of parity on <A11 SoCs. I vaguely remember the edict came down from high that such a parity should exist, and it was implemented in the best way they could within a certain time constraint. They never did that again.

So are caffeine and nicotine, I'm not sure what your point is.

Concerta is extended release methylphenidate. It is not an amphetamine.

This isn't a transformer, it's a diffusion model. You can't split diffusion models across compute nodes.

Just from my limited experience:

Barton Springs in Austin is always brimming with people and Shiner Bock makes a frequent appearance.

Dolores Park in SF never has a dull moment and you can buy shrooms or edibles from vendors walking around.

Golden Gate Park in SF is massive and there are tons of clusters of people socializing and drinking throughout the park (especially near the Conservatory of Flowers!)

Central Park in NY in many ways mirrors Golden Gate Park only its way busier. Good luck finding a spot near the south side of the park on a sunny day. You might spot a mimosa or two, three…

Something is lost as well if you do 'research' by just asking an LLM. On the path to finding your answer in the encyclopedia or academic papers, etc. you discover so many things you weren't specifically looking for. Even if you don't fully absorb everything there's a good chance the memory will be triggered later when needed: "Didn't I read about this somewhere?".

Yep. Though if you don't place any of them - depending on how technical you want to get - that's a DE0.

https://uk.rs-online.com/web/p/d-sub-connectors/0481049 https://uk.rs-online.com/web/p/d-sub-connectors/2748593

It'd be the final piece of Apple's vertical integration puzzle.

I can't comment on MCP use specifically but I can comment on using an LLM while reversing. I use a local instance of whatever ends up being SOTA for local reasoning LLMs at 30B-70B params quantized to 4-6b. I feed it decompiled code to identify functions that are 'tedious' to reverse engineer. I recently reversed a binary that was compiled with soft float and had no symbols or strings. A lot of those functions end up being a ton of bit-twiddling. While I reversed the business logic I had the reasoning model identify the soft float functions with very minimal prompting. It did quite well on those!

I also tried to have it automatically build some structs from code showing the access patterns, and it failed miserably on that task. Likely a larger model (o3 or opus) would do better here.

I personally don't think letting an LLM do large parts of the reversing would be useful to me as I build up a lot of my mental model of the system during the process, so I'd be missing out on that. But for handling annoying bits of code I'd likely just forego otherwise? Go ham!

I'm actually very surprised this happened. I've dis- and reassembled dozens of iPhones (from the iPhone 4 all the way up to the iPhone 16) and I've never torn a single flex cable.

You just have to be careful not to pull on the flex, but the connector instead. This logic applies as much to pulling a plug out of a wall socket as it does a thin flex with a board-to-board connector.

That said, would I characterize disassembling any Apple product as "quite friendly"? No. Do not attempt unless you're either familiar with how things go together or you're willing to spend the money to replace the parts you broke. If those aren't options, find a local repair shop.

Are you saying Nvidia could spin up their own chip fabs in short order?

I can't comment on AMD or Intel but Apple Silicon definitely uses ECC for at least the system level cache. On top of that it performs cache healing (swapping out bad lines for spares) on every cache level every time the system boots.

It’s a slightly more involved project, but tmbinc managed to write arbitrary pictures to a DVD surface:

https://debugmo.de/2022/05/fjita-the-project-that-wasnt-mean...